
"""simple docstring"""


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A_    							=					logging.get_logger(__name__)

A_    							=					{
    """andreasmadsen/efficient_mlm_m0.40""": (
        """https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json"""
    ),
}




class  __lowerCamelCase  ( lowerCAmelCase			):
				a__:      Any          =    'roberta-prelayernorm'




				def __init__(				self							,						UpperCAmelCase=5_0265							,						UpperCAmelCase=768							,						UpperCAmelCase=12							,						UpperCAmelCase=12							,						UpperCAmelCase=3072							,						UpperCAmelCase="gelu"							,						UpperCAmelCase=0.1							,						UpperCAmelCase=0.1							,						UpperCAmelCase=512							,						UpperCAmelCase=2							,						UpperCAmelCase=0.0_2							,						UpperCAmelCase=1e-1_2							,						UpperCAmelCase=1							,						UpperCAmelCase=0							,						UpperCAmelCase=2							,						UpperCAmelCase="absolute"							,						UpperCAmelCase=True							,						UpperCAmelCase=None							,						**UpperCAmelCase							,						):
							super().__init__(pad_token_id=UpperCAmelCase							,						bos_token_id=UpperCAmelCase							,						eos_token_id=UpperCAmelCase							,						**UpperCAmelCase   )

							lowerCamelCase_					=  vocab_size
							lowerCamelCase_					=  hidden_size
							lowerCamelCase_					=  num_hidden_layers
							lowerCamelCase_					=  num_attention_heads
							lowerCamelCase_					=  hidden_act
							lowerCamelCase_					=  intermediate_size
							lowerCamelCase_					=  hidden_dropout_prob
							lowerCamelCase_					=  attention_probs_dropout_prob
							lowerCamelCase_					=  max_position_embeddings
							lowerCamelCase_					=  type_vocab_size
							lowerCamelCase_					=  initializer_range
							lowerCamelCase_					=  layer_norm_eps
							lowerCamelCase_					=  position_embedding_type
							lowerCamelCase_					=  use_cache
							lowerCamelCase_					=  classifier_dropout




class  __lowerCamelCase  ( lowerCAmelCase			):




				@property
				def        UpperCAmelCase__						(				self   ):
							if self.task == "multiple-choice":
										lowerCamelCase_					=  {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
							else:
										lowerCamelCase_					=  {0: '''batch''', 1: '''sequence'''}
							return OrderedDict(
							    [
							        ('''input_ids''', dynamic_axis),
							        ('''attention_mask''', dynamic_axis),
							    ]   )





"""simple docstring"""






from itertools import count




def __magic_name__	(				_lowerCamelCase:		int = 50			)					->						int:

	'''simple docstring'''




	lowerCAmelCase												=  [1] * min_block_length

	for n in count(_lowerCamelCase			):
		fill_count_functions.append(1			)

		for block_length in range(_lowerCamelCase,					n + 1			):
			for block_start in range(n - block_length			):
				fill_count_functions[n] += fill_count_functions[
				    n - block_start - block_length - 1
				]

			fill_count_functions[n] += 1

		if fill_count_functions[n] > 1_000_000:
			break

	return n


if __name__ == "__main__":
					print(f"""{solution() = }""")


